Engineering design as an information-processing activity. Part 2: Information sources and processing

1971 ◽  
Vol 17 (6) ◽  
pp. 233 ◽  
Author(s):  
P.A. Shears
Keyword(s):  
Information Processing ◽  
Engineering Design ◽  
Information Sources ◽  
Processing Activity

Information processing by elderly consumers: a five-decade review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gianluigi Guido ◽  
Marco Pichierri ◽  
Cristian Rizzo ◽  
Verdiana Chieffi ◽  
George Moschis
Keyword(s):  
Information Processing ◽  
Design Methodology ◽  
State Of The Art ◽  
Relevant Literature ◽  
Academic Research ◽  
The Elderly ◽  
Marketing Strategies ◽  
Content Type ◽  
Processing Activity ◽  
Elderly Consumers

Purpose The purpose of this study is to review scholarly research on elderly consumers’ information processing and suggest implications for services marketing. Design/methodology/approach The review encompasses a five-decade period (1970–2018) of academic research and presents relevant literature in four main areas related to information processing: sensation, attention, interpretation and memory. Findings The study illustrates how each of the aforementioned phases of the information processing activity may affect how elderly individuals buy and consume products and services, emphasizing the need for a better comprehension of the elderly to develop effectual marketing strategies. Originality/value The study provides readers with detailed state-of-the-art knowledge about older consumers’ information processing, offering a comprehensive review of academic research that companies can use to improve the effectiveness of their marketing efforts that target the elderly market.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

Information sources and investing decisions – a path modeling approach

2017 ◽  
Vol 43 (8) ◽  
pp. 928-947 ◽  
Author(s):  
Mohammad Tariqul Islam Khan ◽  
Siow-Hooi Tan ◽  
Lee-Lee Chong
Keyword(s):  
Information Processing ◽  
Stock Market ◽  
Institutional Investors ◽  
Information Sources ◽  
Stock Exchange ◽  
Information Source ◽  
Limited Information ◽  
Sources Of Information ◽  
Path Modeling ◽  
Content Type

Purpose Given the special feature of institutional investors in Malaysia, the purpose of this paper is to explore how these investors acquire and employ different information sources in their investing decisions. Design/methodology/approach The study uses self-reported information sources collected via a survey of 66 institutional investors following convenience sampling, and estimates the relationship via Smart-PLS (Partial Least Squares) path modeling. Findings The results suggest that although investors place greater importance on fundamental and technical indicators, they do not implement these information sources in their decisions. Rather, gathering information from economic statistics and ratios, discussion with colleagues, historical returns of the Malaysian stock market, decisions of other market players, specialized press and stock exchange bulletins, and statements of opinion leaders are more closely related to trading, risk taking, and financial asset holding. This finding supports the limited information processing of bounded rationality, irrespective of the type of information source. Practical implications Institutional investors should critically assess the information sources upon which they rely to collect information as irrational information processing may adversely affect the stock market efficiency. Originality/value To the authors’ knowledge, this is the first study to explore the unique features of institutional investors in Malaysia in conjunction with their sources of information, and to identify which sources matter when making investing decisions.

scholarly journals Descriptive Models of Sequential Decisions in Engineering Design: An Experimental Study

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Ashish M. Chaudhari ◽  
Ilias Bilionis ◽  
Jitesh H. Panchal
Keyword(s):  
Engineering Design ◽  
Information Acquisition ◽  
Model Comparison ◽  
Information Sources ◽  
Primary Objective ◽  
Monetary Incentives ◽  
Bayesian Model Comparison ◽  
Fixed Budget ◽  
Subject Experiment ◽  
The Eu

Abstract Engineering design involves information acquisition decisions such as selecting designs in the design space for testing, selecting information sources, and deciding when to stop design exploration. Existing literature has established normative models for these decisions, but there is lack of knowledge about how human designers make these decisions and which strategies they use. This knowledge is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. Therefore, the primary objective in this study is to identify models that provide the best description of a designer’s information acquisition decisions when multiple information sources are present and the total budget is limited. We conduct a controlled human subject experiment with two independent variables: the amount of fixed budget and the monetary incentive proportional to the saved budget. By using the experimental observations, we perform Bayesian model comparison on various simple heuristic models and expected utility (EU)-based models. As expected, the subjects’ decisions are better represented by the heuristic models than the EU-based models. While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The net payoff using heuristic models is closer to the EU-based models in experimental treatments where the budget is low and there is incentive for saving the budget. This indicates the potential for nudging designers’ decisions toward maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to saved budget.

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